I was culling out books, mostly obsolete technical books, and I remembered that I have an extra copy of Feller’s classic probability text. It’s volume 1, second edition. If you’re a student and would like the book, please send me an email with your mailing address.
Update: The book was claimed 11 minutes after this post was published.
The subtitle of That Hideous Strength is “A Modern Fairy-Tale for Grown-Ups.” C. S. Lewis explains in the preface why the book begins with mundane scenes even though he calls it a fairy tale.
If you ask why—intending to write about magicians, devils, pantomime animals, and planetary angels—I nevertheless begin with such hum-drum scenes and persons, I reply that I am following the traditional fairy-tale. We do not always notice its method, because the cottages, castles, woodcutters, and petty kings with which a fairy-tale opens have become for us as remote as the witches and ogres to which it proceeds. But they were not remote at all to the men who made and first enjoyed the stories.
The second chapter of Out of the Silent Planet opens by describing a room as “a strange mixture of luxury and squalor.” It gives examples such as the room as having fine armchairs but no carpets or curtains, strewn with debris. The room has “empty champagne-bottles” and “teacups a quarter full of tea and cigarette-ends.” The room belongs to a scientist and an investor who have the resources to live in beauty and comfort, but instead have a few luxurious items in a pigsty. The scene is a metaphor for science and business detached from humane uses, one of the themes of the book.
Many people have drawn Venn diagrams to locate machine learning and related ideas in the intellectual landscape. Drew Conway’s diagram may have been the first. It has at least been frequently referenced.
By this classification, Hector Cuesta’s new book Practical Data Anaysis is located toward the “hacking skills” corner of the diagram. No single book can cover everything, and this one emphasizes practical software knowledge more than mathematical theory or details of a particular problem domain.
The biggest strength of the book may be that it brings together in one place information on tools that are used together but whose documentation is scattered. The book is great source for sample code. The source code is available on GitHub, though it’s more understandable in the context of the book.
Much of the book uses Python and related modules and tools including:
It also uses D3.js (with JSON, CSS, HTML, …), MongoDB (with MapReduce, Mongo Shell, PyMongo, …), and miscellaneous other tools and APIs.
There’s a lot of material here in 360 pages, making it a useful reference.
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I’ve enjoyed reading The New York Times Book of Physics and Astronomy, ISBN 1402793200, a collection of 129 articles written between 1888 and 2012. Its been much more interesting than its mathematical predecessor. I’m not objective — I have more to learn from a book on physics and astronomy than a book on math — but I think other readers might also find this new book more interesting.
I was surprised by the articles on the bombing of Hiroshima and Nagasaki. New York Times reporter William Lawrence was allowed to go on the mission over Nagasaki. He was not on the plane that dropped the bomb, but was in one of the other B-29 Superfortresses that were part of the mission. Lawrence’s story was published September 9, 1945, exactly one month later. Lawrence was also allowed to tour the ruins of Hiroshima. His article on the experience was published September 5, 1945. I was surprised how candid these articles were and how quickly they were published. Apparently military secrecy evaporated rapidly once WWII was over.
Another thing that surprised me was that some stories were newsworthy more recently than I would have thought. I suppose I underestimated how long it took to work out the consequences of a major discovery. I think we’re also biased to think that whatever we learned as children must have been known for generations, even though the dust may have only settled shortly before we were born.
When I was in grad school, my advisor asked me to study his out-of-print book, Hilbert Space Methods in Partial Differential Equations. I believe I had a photocopy of a photocopy; I don’t recall ever seeing the original book. I pored over that stack of copies line by line while preparing for my qualifying exams.
Then this evening I was browsing a used book store and was shocked to find a copy of the book, a Dover reprint (ISBN 0486474437).
It was an odd feeling to find what was once a precious and mysterious book available for $5.99 as part of a rag-tag assortment of mostly elementary/popular used math books.
Like all the books in the series, The Drug Book is a collection of alternating one-page articles and full page color photographs, arranged chronologically. These books make great coffee table books because they’re colorful and easy to dip in and out of. The other books in the series are The Space Book, The Physics Book, and The Medical Book.
The book’s definition of “drug” is a little broad. In addition to medicines, it also includes related chemicals such as recreational drugs and poisons. It also includes articles on drug-related reference works and legislation.
I ran across a copy of 21st Century C (ISBN 1491903899) this afternoon. I hadn’t heard of the book, but the title was intriguing. I wrote more C in the 20th century than the 21st, so my ideas regarding C (sans ++) are out of date. (I’ve written a fair amount of C++ this century, but I have only written C under duress and with difficulty.)
I’ve only skimmed through the book so far, but one thing I like about it is that the first 100 pages are devoted to tools, not the C language per se. There’s a lot more to using any language than the language itself, and I find it harder to learn about tools than languages. It’s hard to know what tools to learn, and what features of those tools to learn first.
The approach I have taken here is to try to move always from the particular to the general, following through the steps of the abstraction process until the abstract concept emerges naturally. … at the finish it would be quite appropriate for the reader to feel that (s)he had just arrived at the subject, rather than reached the end of the story.
There’s a new book on SymPy, a Python library for symbolic math.
The book is Instant SymPy Starter by Ronan Lamy. As far as I know, this is the only book just on SymPy. It’s only about 50 pages, which is nice. It’s not a replacement for the online documentation but just a quick start guide.
The online SymPy documentation is good, but I think it would be easier to start with this book. And although I’ve been using SymPy off and on for a while, I learned a few things from the book.
The subtitle may be a little misleading. There is a fair amount of math in the book, but the ratio of history to math is pretty high. You might say the book is more about the role of mathematicians than the role of mathematics. As Roger Penrose says on the back cover, the book has “illuminating descriptions and minimal technicality.”
Someone interested in weather prediction but without a strong math background would enjoy reading the book, though someone who knows more math will recognize some familiar names and theorems and will better appreciate how they fit into the narrative.
SciPy and NumPy (ISBN 1449305466) by Eli Bressert is the smallest book I’ve seen from O’Reilly, aside from books in their pocket guide series. The SciPy and NumPy libraries are huge, and it can be hard to know where to start. This book gives a good, brisk overview. In addition to SciPy and NumPy, the it also gives a brief introduction to SciKit, in particular scikit-learn for machine learning and scikit-image for image processing.
(Eli told me that he is working on supplementary material for the book. Everyone who bought the book electronically will automatically receive the new material when it is available.)
Python for Kids (ISBN 1593274076) by Jason R. Briggs is an introduction to programming aimed at kids. It starts with with an introduction to Python and moves to developing a simple game. It seems to me that kids would find the book interesting. It’s about seven times longer than the SciPy and NumPy book. It moves at a slow pace, has many illustrations, and has a casual tone.
NumPy Cookbook by Ival Idris contains around 70 small recipes, about three pages each. Many of these are about NumPy itself, but the book covers much more than its title would imply. Out of 10 chapters, four are strictly about NumPy. The first chapter of the book is about IPython. Another chapter is about “connecting NumPy with the rest of the world,” i.e. interfacing with Java, R, Matlab, and cloud services. Two chapters are devoted to profiling, debugging, and optimizing performance. There is a chapter on quality assurance (static analysis, unit testing, and documentation). And the final chapter is about Scikits and Pandas.
PowerShell was written first and foremost for Windows system administrators, and the benefits to this community are clear. It’s not as clear what developers should make of PowerShell.
Administrators can learn PowerShell as a shell first, and gradually transition from interactive use to scripting. They may learn PowerShell as their first programming language and not even give too much thought to the language per se. But a developer has to ask why and when to use PowerShell rather than another language, such as C#.
Doug Finke’s new book Windows PowerShell for Developers (ISBN 1449322700) is “for developers” in a couple ways. First, the style of the book is geared toward developers. The book is small, less than 200 pages, because the author assumes the readers are experienced Windows developers who want to focus on what PowerShell adds to what they already know. Second, the book focuses on tasks a developer might want to do. Rather than show you how to create a new Active Directory user, as many PowerShell books would, this book covers topics such as
interfacing with C#
embedding PowerShell in your application
working with XML and JSON
interfacing with Excel
So why should software developers use PowerShell? And what tasks should they do in PowerShell? One answer to the first question, implicit in the book’s examples, is that PowerShell makes it possible to carry out common tasks with little code. Another answer explicitly given in the book is integration.
Given PowerShell’s growing integration with the rest of the Windows platform, as PowerShell grows, so does your application.”
The book is full of examples of what tasks a developer might want to do in PowerShell. The examples I found most interesting were embedding PowerShell to provide a scripting language for your application and creating DSLs in PowerShell.
One pattern in the examples is text munging, whether that text is source code or common data file formats. Another pattern is integration, especially integrating Microsoft technologies. PowerShell is designed to make it possible to solve these kinds of problems with a minimum of ceremony.
I’ll close with a couple reasons why might a developer not want to use PowerShell in my opinion. The first is frequency of use. Although PowerShell can solve many problems with significantly less code than C# would require, you have to learn PowerShell first, and you have to use it frequently enough to remember it. You have to use PowerShell enough to repay the time invested in learning and practicing it.
The second reason is size. The C# language and the Visual Studio IDE were designed for large projects, but scale down fairly well for smaller projects. PowerShell was designed for the command line, but scales fairly well for large scripts. If you use PowerShell and C#, you’ll have to decide at what size you want to switch from one language to the other.